The AI Agent Revolution: From Hype to Hard Reality
German corporations are facing a critical challenge: the rapid adoption of AI agents is outpacing their IT infrastructure’s ability to handle the influx. While the technology is being deployed at breakneck speed, security and integration are lagging, creating a potentially costly vulnerability.
Explosive Growth, Emerging Chaos
A recent report, the State of AI Agent Security 2026 by Gravitee, reveals that 81 percent of IT teams are already testing or actively using AI agents. Salesforce data corroborates this trend, indicating that companies currently deploy an average of twelve different AI agents. This number is projected to surge by 67 percent within the next two years.
The Siloed Agent Problem
Despite the widespread adoption, a fundamental issue is emerging. According to Salesforce, half of all AI agents operate in isolation, unable to share data or coordinate actions. One IT consultant described the situation as having “brilliant individual players sitting in different departments, but not speaking a common language.” This lack of integration is compounded by existing IT challenges: 96 percent of companies struggle with data silos, and only 27 percent of applications are fully integrated.
Shadow AI and the EU AI Act
Many organizations are overlooking the requirements of the EU AI Act, creating a “Shadow AI” governance gap. The Act mandates labeling, risk assessment, and comprehensive documentation for AI systems, with potential fines and operational risks for non-compliance.
The Rise of Agent Orchestration
In response to the integration challenges, a new software market is emerging: platforms for orchestrating AI agents. These systems aim to coordinate specialized agents, manage their communication, and oversee complex workflows. Companies like Kinaxis, with its Maestro Agent Studio platform, and Ibexa are leading the charge, alongside cloud giants Microsoft, Google, and AWS, all investing heavily in agent orchestration capabilities.
Security Risks: A Growing Concern
The speed of deployment has created a dangerous security vacuum. The Gravitee report highlights that 88 percent of organizations have experienced or suspect security incidents involving AI agents in the past year. An estimated 1.5 million agents are currently operating without adequate oversight – a phenomenon known as “Shadow AI.” Only 14.4 percent of AI agents are launched with full approval from IT security departments.
From LLMs to LAMs: The Next Evolution
The current wave of autonomy is driven by a shift from Large Language Models (LLMs), like ChatGPT, which excel at understanding and generating text, to Large Action Models (LAMs). LAMs are designed to translate intentions into concrete, executable actions. This evolution is crucial for complex workflows, such as invoice processing or software testing, which require a planned sequence of actions across multiple applications. The market for agentic AI is projected to grow from €7.8 billion to over €52 billion by 2030, fueled by more powerful LAMs.
Agentic Debt: The Cost of Disintegration
The industry has moved beyond the experimental phase. A Gartner study previously showed that 75 percent of firms were testing agents, but only 15 percent deployed fully autonomous systems. Now, in early 2026, AI agents are migrating from isolated pilot projects into core business processes. The biggest obstacles are no longer the capabilities of the AI models themselves, but the lack of preparedness within corporate IT. Companies that fail to address this gap risk accumulating “agentic debt” – a sprawling landscape of isolated, uncontrolled agents that create more complexity than value.
Pro Tip
FAQ
Q: What is “Shadow AI”?
A: AI systems deployed without proper IT security oversight, creating potential risks related to data breaches, compliance, and control.
Q: What are LAMs?
A: Large Action Models are a new generation of AI models designed to translate intentions into concrete actions, enabling AI agents to perform tasks beyond simply generating text.
Q: What is agent orchestration?
A: The process of coordinating and managing multiple AI agents to perform together effectively, sharing data and automating complex workflows.
Q: Is my company compliant with the EU AI Act?
A: The EU AI Act requires labeling, risk assessment, and documentation for AI systems. Many companies are currently unprepared for these requirements.
Did you know? The market for agentic AI is expected to exceed €52 billion by 2030.
Want to learn more about navigating the complexities of AI agent implementation? Explore our other articles on AI-driven transformation and IT security best practices.
